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FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images
COVID-19 is an acronym for coronavirus disease 2019. Initially, it was called 2019-nCoV, and later International Committee on Taxonomy of Viruses (ICTV) termed it SARS-CoV-2. On 30th January 2020, the World Health Organization (WHO) declared it a pandemic. With an increasing number of COVID-19 cases...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106902/ http://dx.doi.org/10.1007/s12530-021-09385-2 |
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author | Agrawal, Tarun Choudhary, Prakash |
author_facet | Agrawal, Tarun Choudhary, Prakash |
author_sort | Agrawal, Tarun |
collection | PubMed |
description | COVID-19 is an acronym for coronavirus disease 2019. Initially, it was called 2019-nCoV, and later International Committee on Taxonomy of Viruses (ICTV) termed it SARS-CoV-2. On 30th January 2020, the World Health Organization (WHO) declared it a pandemic. With an increasing number of COVID-19 cases, the available medical infrastructure is essential to detect the suspected cases. Medical imaging techniques such as Computed Tomography (CT), chest radiography can play an important role in the early screening and detection of COVID-19 cases. It is important to identify and separate the cases to stop the further spread of the virus. Artificial Intelligence can play an important role in COVID-19 detection and decreases the workload on collapsing medical infrastructure. In this paper, a deep convolutional neural network-based architecture is proposed for the COVID-19 detection using chest radiographs. The dataset used to train and test the model is available on different public repositories. Despite having the high accuracy of the model, the decision on COVID-19 should be made in consultation with the trained medical clinician. |
format | Online Article Text |
id | pubmed-8106902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-81069022021-05-10 FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images Agrawal, Tarun Choudhary, Prakash Evolving Systems Original Paper COVID-19 is an acronym for coronavirus disease 2019. Initially, it was called 2019-nCoV, and later International Committee on Taxonomy of Viruses (ICTV) termed it SARS-CoV-2. On 30th January 2020, the World Health Organization (WHO) declared it a pandemic. With an increasing number of COVID-19 cases, the available medical infrastructure is essential to detect the suspected cases. Medical imaging techniques such as Computed Tomography (CT), chest radiography can play an important role in the early screening and detection of COVID-19 cases. It is important to identify and separate the cases to stop the further spread of the virus. Artificial Intelligence can play an important role in COVID-19 detection and decreases the workload on collapsing medical infrastructure. In this paper, a deep convolutional neural network-based architecture is proposed for the COVID-19 detection using chest radiographs. The dataset used to train and test the model is available on different public repositories. Despite having the high accuracy of the model, the decision on COVID-19 should be made in consultation with the trained medical clinician. Springer Berlin Heidelberg 2021-05-09 2022 /pmc/articles/PMC8106902/ http://dx.doi.org/10.1007/s12530-021-09385-2 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Agrawal, Tarun Choudhary, Prakash FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images |
title | FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images |
title_full | FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images |
title_fullStr | FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images |
title_full_unstemmed | FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images |
title_short | FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images |
title_sort | focuscovid: automated covid-19 detection using deep learning with chest x-ray images |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106902/ http://dx.doi.org/10.1007/s12530-021-09385-2 |
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